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        Note that additional data was saved in multiqc_data_1 when this report was generated.


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        If you use plots from MultiReport in a publication or presentation, please cite:

        MultiReport: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

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        About MultiReport

        This report was generated using MultiReport, version 1.9

        You can see a YouTube video describing how to use MultiReport reports here: https://youtu.be/qPbIlO_KWN0

        For more information about MultiReport, including other videos and extensive documentation, please visit http://multiqc.info

        You can report bugs, suggest improvements and find the source code for MultiReport on GitHub: https://github.com/ewels/MultiQC

        MultiReport is published in Bioinformatics:

        MultiReport: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

        A modular tool to aggregate results from ClinicoOmics App into a single report.

        Report generated on 2021-01-21, 11:47 based on data in ClinicoOmics.


        Supplementary

        supplementary is a module to show the additional information about this quality assessment report.

        Method

        We use FastQC, FastQ Screen, Qualimap and MultiQC to evaluate the quality of sequencing data. [1] RNA-seq quality control consists of pre-alignment, post-alignment and quantification quality control.

        Pre-alignment quality control focuses on raw fastq files and helps to determine systematic bias and library issue, such as sequencing quality issue, high GC or AT, PCR bias, adapter contaminant, cross species contamination. Fastqc [2] and fastqscreen [3] are used to evaluate raw reads quality.

        Post-alignment quality control focuses on bam files and helps to measure library performance and sample variance, such as sequencing error rate, sequencing depth and coverage consistency. Qualimap [4] is used to evaluate quality of bam files.

        Quantification quality control is to evaluate the data quality from a set of data quality control metrics and thresholds, especially discrimination of different groups.

        Software

        Fastqc
        v0.11.5
        Fastqscreen
        v0.12.0
        Qualimap
        v2.0.0
        MultiQC
        v1.9

        Contact Us

        Fudan University Pharmacogenomics Research Center

        Project Manager Zhihui Li

      • Phone: 15200852771
      • Email: 18210700119@fudan.edu.cn
      • Disclaimer

        This quality control report is only for this specific test data set and doesn’t represent an evaluation of the business level of the sequencing company. This report is only used for scientific research, not for clinical or commercial use. We don’t bear any economic and legal liabilities for any benefits or losses (direct or indirect) from using the results of this report.